Templates / Predict F1 Race Winners with OpenAI GPT-4o, Historical Data & Slack Alerts

Predict F1 Race Winners with OpenAI GPT-4o, Historical Data & Slack Alerts

Ready for 3.0

by Cheng Siong Chin ✓ · 236 views · created 2025-11-16 · Miscellaneous, AI Summarization

Ready for 3.0. This template uses no nodes that n8n 3.0 removes. No removed nodes, versions or helpers found. Static check, last run 2026-10-19.

Nodes used (17)

AI AgentOpenAI Chat ModelHTTP RequestSimple Vector StoreEmbeddings OpenAIDefault Data LoaderRecursive Character Text SplitterPostgresSlackGoogle SheetsCode

What it does

How It Works Every day at 8 AM, the workflow automatically retrieves the latest F1 data—including driver standings, qualifying results, race schedules, and circuit information. All sources are merged into a unified dataset, and driver performance metrics are computed using historical trends. An AI agent, enhanced with vectorized race history, evaluates patterns and generates race-winner predictions. When the confidence score exceeds the defined threshold, the system pushes an automated Slack alert and records the full analysis in the database and Google Sheets. Setup Steps 1. Update the workflow configuration with: newsApiUrl, weatherApiUrl, historicalYears, and confidenceThreshold. 2. Connect PostgreSQL using the schema: predictiondate, predictedwinner, confidencescore, predictionsource, dataversion, fullanalysis. 3. Provide the Slack channel ID for sending high-confidence alerts. 4. Specify the Google Sheets document ID and sheet name for prediction logging. 5. Test connectivity to the Ergast API (no authentication required). Prerequisites OpenAI account (GPT-4o access), Slack workspace admin access, PostgreSQL instance, Google Sheets account, n8n instance with LangChain community nodes enabled. Customization Extend by adding constructor predictions (modify AI prompt). Integrate Discord or Teams instead of Slack. Benefits Saves time by automating data collection, improves accuracy using multiple performance metrics and historical patterns.

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